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Chronic disease
P2-295 Socio-demographic patterns of physical activity in India: a cross sectional study
  1. R Sullivan1,
  2. S Kinra1,
  3. U Ekelund2,
  4. A V Bharathi3,
  5. T Collier1,
  6. M Vaz4,
  7. A Kurpad4,
  8. K S Reddy7,
  9. D Prabhakaran5,6,
  10. H Kuper1,
  11. S Ebrahim1,6
  1. 1London School of Hygiene & Tropical Medicine, London, UK
  2. 2MRC Epidemiology Unit, Cambridge, UK
  3. 3Indira Gandhi Open University, Bangalore, India
  4. 4St John's Research Institute, Bangalore, India
  5. 5Centre for Chronic Disease Control, New Delhi, India
  6. 6South Asia Network for Chronic Disease, Public Health Foundation of India, New Delhi, India
  7. 7Public Health Foundation of India, New Delhi, India


Introduction The existence of a socio-demographic patterns of cardiovascular disease (CVD) in India has been suggested, with a higher CVD risk in individuals: from urban areas, the south, higher socio-economic status (SES), and in the elderly. Whether this pattern is replicated in physical activity (PA) is unknown. We aimed to examine the socio-demographic pattern of PA in India using the Indian Migration Study (IMS); a cross-sectional sib-pair designed survey.

Methods The IMS included a PA questionnaire (IMS-PAQ). We recruited 6995 participants (41% female, 37% rural) whose PA was characterised over the last month. We estimated (1) total activity (MET hr/day), (2) PA Level defined as inactive <1.4, low active 1.4–1.59, active 1.6–1.89 and very active ≥1.9, and (iii) sedentary behaviour (min/day). These were compared with socio-demographic status (age, sex, urban/rural, north/south) and socio-economic status (SES) using regression analyses, adjusting for confounders and clustering.

Results Total activity decreased with age and SES, and was lower in women, among urban participants and in the south (p<0.001). These findings held true for PA Level where the proportion classified as active or very active was lower in women (38% vs 54% men), in the highest SES group (37% vs 61% lowest SES group), in urban participants (40% vs 60% rural) and in the south (43% vs 52% north). This pattern reversed for sedentary behaviour as older participants, women, south and urban residents and higher SES groups were significantly more sedentary.

Conclusion PA patterning broadly mirrors that of CVD in India. Further studies should investigate how PA patterns may modify risk of CVD in India.

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